Enhancing Multi-Turn Dialogue Generation with MoE-Based Multi-Latent Variable Fusion

Generating relevant and diverse responses remains challenging for non-pretrained small models in open-domain multi-turn dialogues. To address the one-to-many mapping problem caused by conversational uncertainty, we propose a novel framework integrating Variational Autoencoder (VAE) with a Mixture-of...

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Veröffentlicht in:	2025 IEEE 6th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT) S. 1 - 4
Hauptverfasser:	Cui, Zishun, Sun, Xiao
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 11.04.2025
Schlagworte:	Artificial intelligence Autoencoders Context modeling Dialogue generation Diversity reception Information technology Latent variables Mixture of Experts Multi-turn dialogue Seminars Uncertainty Variational Autoencoder
Online-Zugang:	Volltext
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